• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.45-51
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• 2017

In this paper, we propose a consecutive-frame super-resolution method to tackle a moving object problem. The super-resolution is a method restoring a high resolution image from a low resolution image. The super-resolution is classified into two types, briefly, single-frame super-resolution and consecutive-frame super-resolution. Typically, the consecutive-frame super-resolution recovers a better than the single-frame super-resolution, because it use more information from consecutive frames. However, the consecutive-frame super-resolution failed to recover the moving object. Therefore, we proposed an improved method via moving object detection. Experimental results showed that the proposed method restored both the moving object and the background properly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3217-3238
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• 2018

In this paper, a depth image up-sampling method is put forward by using pixel classifying and jointed bilateral filtering. By analyzing the edge maps originated from the high-resolution color image and low-resolution depth map respectively, pixels in up-sampled depth maps can be classified into four categories: edge points, edge-neighbor points, texture points and smooth points. First, joint bilateral up-sampling (JBU) method is used to generate an initial up-sampling depth image. Then, for each pixel category, different refinement methods are employed to modify the initial up-sampling depth image. Experimental results show that the proposed algorithm can reduce the blurring artifact with lower bad pixel rate (BPR).

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.6
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• pp.868-876
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• 2005

Silk fabrics were dyed with yellow natural materials. Gardenia, turmeric, amur cork tree, safflower, Japanese pagoda tree, and onion were used as natural materials. Color image of natural dyed silk fabrics was classified by 4 factors(Cheerfulness, Comfortness, Pastrol, Revealation). Cheerfulness factor affected significantly with color image. Amur cork tree or turmeric dyed fabrics were shown as light and cute, safflower or gardenia dyed fabric shown as comfort, and onion dyed fabrics shown as mature and simple. Color image with specialty was significant difference in Preference and Revelation factor. Preference was appeared as amur cork tree>turmeric>gardenia>safflower>Japanese pagoda tree>onion.

• Archives of design research
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• v.11 no.1
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• pp.269-278
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• 1998

Along with the development of the video-film related industry, the need for establishing the education of the video image design is now rapidly growing in a variety of video art institutes. The video image design IS therefore being more classified and systematized than ever to maxImize its effectivity and facilitate its creativity. This paper is thus aimed to suggest the basic curriculum and project class schedule on the video image design which can be utilized in class activities.

• The Journal of Natural Sciences
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• v.8 no.2
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• pp.77-82
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• 1996

New very low bit rate segmentation image coding technique is proposed by segmenting image into textually homogeneous regions. Regions are classified into on of three perceptually distinct texture classes (perceived constant intensity (class I), smooth texture (class II), and rough texture (class III) using the human Visual System (HVS) and the fractals. To design very low bit rate image coder, it is very important to determine nonoverlap and overlap segmentation method for each texture class. Good quality reconstructed images are obtained with about 0.10 to 0.21 bit per pixel (bpp) for many different types of imagery.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.597-605
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• 1999

In this paper, we propose a cardioangiography sequence image coding scheme which use a subtraction between initial image and current frame inserted contrast dye. Stable regions are obtained by the multithreshold and meaningful region is extracted by the images with stable region. The image with meaningful region is classified into contour and texture information. Contour information is coded by contour coding. And texture information is approximated by two-dimensional polynomial function and each coefficients is coded. Experimental results confirm that the sequence of cardioangiography are well reconstructed at the low bit rate (0.02∼0.04 bpp) and high compression ratio.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.311-312
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• 2018

This paper proposes an image processing system based on the Convolution Neural Network technique. The image classification was performed using the composite neural network model and the images were classified with accuracy of 84% or more. The proposed system is implemented to operate on various platforms. When the system is used in the classification of images, the efficiency is higher because it is higher than the accuracy of the existing model.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.1035-1038
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• 2007

In this paper, we propose a color image improvement method. The proposed algorithms are classified with the adaptive contrast stretching method for contrast enhancement and the adaptive saturation enhancement method for saturation enhancement. The adaptive contrast stretching method is to compensate a significant change of brightness while luminance is processed. The adaptive saturation enhancement method inhibits its saturation from de-saturation and oversaturation while chrominance is processed. The proposed algorithms are focused on a preference color processing in order to generate better image quality than the algorithms focused on a uniform color processing for human vision.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.5
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• pp.560-569
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• 2003

The purpose of this study was to investigate the usage condition of avatar, the clothing images of avatars, and the difference of self images among avatar user groups which were clustered by the clothing image of using avatar. Avatars were decorated not only to get personal satisfaction and joyfulness but also to realize the desire of relationship with other people. The clothing images of avatars were classified into 7 factors, which were labeled as cute, mature, sexy, old-fashion, unisex. and unique factors. There were no significant differences in self images among 3 avatar user groups which were clustered by 7 factors of clothing images. The result indicated that avatar users pursued various clothing images for their avatar, however, no significant relations were existed between avatar＇s images and user＇s self images and further studies would be required to find out significant variables which determined avatar＇s clothing images.

• IE interfaces
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• v.11 no.2
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• pp.119-124
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• 1998

This paper proposes a new part family classification system (IPFACS: Image Processing and Fuzzy ART based Clustering System), which incorporates image processing techniques and a modified fuzzy ART neural network algorithm. IPFACS can classify parts based on geometrical shape and manufacturing attributes, simultaneously. With a proper reduction and normalization of an image data through the image processing methods and adding method in the modified Fuzzy ART, different types of geometrical shape data and manufacturing attribute data can be simultaneously classified in the same system. IPFACS has been tested for an example set of hypothetical parts. The results show that IPFACS provides a good feasible approach to form families based on both geometrical shape and manufacturing attributes.